Python: [BREAKING] Renamed create_agent to as_agent (#3249)

* Renamed create_agent to as_agent

* Override for as_agent

* Added override

python/samples/getting_started/workflows/agents/azure_ai_agents_streaming.py

@@ -27,7 +27,7 @@ Prerequisites:
 
 
 def create_writer_agent(client: AzureAIAgentClient) -> ChatAgent:
-    return client.create_agent(
+    return client.as_agent(
         name="Writer",
         instructions=(
             "You are an excellent content writer. You create new content and edit contents based on the feedback."
@@ -36,7 +36,7 @@ def create_writer_agent(client: AzureAIAgentClient) -> ChatAgent:
 
 
 def create_reviewer_agent(client: AzureAIAgentClient) -> ChatAgent:
-    return client.create_agent(
+    return client.as_agent(
         name="Reviewer",
         instructions=(
             "You are an excellent content reviewer. "

python/samples/getting_started/workflows/agents/azure_chat_agents_function_bridge.py

@@ -87,7 +87,7 @@ async def enrich_with_references(
 
 
 def create_research_agent():
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="research_agent",
         instructions=(
             "Produce a short, bullet-style briefing with two actionable ideas. Label the section as 'Initial Draft'."
@@ -96,7 +96,7 @@ def create_research_agent():
 
 
 def create_final_editor_agent():
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="final_editor_agent",
         instructions=(
             "Use all conversation context (including external notes) to produce the final answer. "

python/samples/getting_started/workflows/agents/azure_chat_agents_streaming.py

@@ -27,7 +27,7 @@ Prerequisites:
 
 
 def create_writer_agent():
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=(
             "You are an excellent content writer. You create new content and edit contents based on the feedback."
         ),
@@ -36,7 +36,7 @@ def create_writer_agent():
 
 
 def create_reviewer_agent():
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         instructions=(
             "You are an excellent content reviewer."
             "Provide actionable feedback to the writer about the provided content."

python/samples/getting_started/workflows/agents/azure_chat_agents_tool_calls_with_feedback.py

@@ -168,7 +168,7 @@ class Coordinator(Executor):
 
 def create_writer_agent() -> ChatAgent:
     """Creates a writer agent with tools."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="writer_agent",
         instructions=(
             "You are a marketing writer. Call the available tools before drafting copy so you are precise. "
@@ -182,7 +182,7 @@ def create_writer_agent() -> ChatAgent:
 
 def create_final_editor_agent() -> ChatAgent:
     """Creates a final editor agent."""
-    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
         name="final_editor_agent",
         instructions=(
             "You are an editor who polishes marketing copy after human approval. "

python/samples/getting_started/workflows/agents/concurrent_workflow_as_agent.py

@@ -28,7 +28,7 @@ async def main() -> None:
     # 1) Create three domain agents using AzureOpenAIChatClient
     chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
-    researcher = chat_client.create_agent(
+    researcher = chat_client.as_agent(
         instructions=(
             "You're an expert market and product researcher. Given a prompt, provide concise, factual insights,"
             " opportunities, and risks."
@@ -36,7 +36,7 @@ async def main() -> None:
         name="researcher",
     )
 
-    marketer = chat_client.create_agent(
+    marketer = chat_client.as_agent(
         instructions=(
             "You're a creative marketing strategist. Craft compelling value propositions and target messaging"
             " aligned to the prompt."
@@ -44,7 +44,7 @@ async def main() -> None:
         name="marketer",
     )
 
-    legal = chat_client.create_agent(
+    legal = chat_client.as_agent(
         instructions=(
             "You're a cautious legal/compliance reviewer. Highlight constraints, disclaimers, and policy concerns"
             " based on the prompt."

python/samples/getting_started/workflows/agents/custom_agent_executors.py

@@ -43,7 +43,7 @@ class Writer(Executor):
 
     def __init__(self, id: str = "writer"):
         # Create a domain specific agent using your configured AzureOpenAIChatClient.
-        self.agent = AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+        self.agent = AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
             instructions=(
                 "You are an excellent content writer. You create new content and edit contents based on the feedback."
             ),
@@ -85,7 +85,7 @@ class Reviewer(Executor):
 
     def __init__(self, id: str = "reviewer"):
         # Create a domain specific agent that evaluates and refines content.
-        self.agent = AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+        self.agent = AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
             instructions=(
                 "You are an excellent content reviewer. You review the content and provide feedback to the writer."
             ),

python/samples/getting_started/workflows/agents/group_chat_workflow_as_agent.py

@@ -35,7 +35,7 @@ async def main() -> None:
     workflow = (
         GroupChatBuilder()
         .with_agent_orchestrator(
-            OpenAIChatClient().create_agent(
+            OpenAIChatClient().as_agent(
                 name="Orchestrator",
                 instructions="You coordinate a team conversation to solve the user's task.",
             )

python/samples/getting_started/workflows/agents/handoff_workflow_as_agent.py

@@ -66,7 +66,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
         Tuple of (triage_agent, refund_agent, order_agent, return_agent)
     """
     # Triage agent: Acts as the frontline dispatcher
-    triage_agent = chat_client.create_agent(
+    triage_agent = chat_client.as_agent(
         instructions=(
             "You are frontline support triage. Route customer issues to the appropriate specialist agents "
             "based on the problem described."
@@ -75,7 +75,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
     )
 
     # Refund specialist: Handles refund requests
-    refund_agent = chat_client.create_agent(
+    refund_agent = chat_client.as_agent(
         instructions="You process refund requests.",
         name="refund_agent",
         # In a real application, an agent can have multiple tools; here we keep it simple
@@ -83,7 +83,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
     )
 
     # Order/shipping specialist: Resolves delivery issues
-    order_agent = chat_client.create_agent(
+    order_agent = chat_client.as_agent(
         instructions="You handle order and shipping inquiries.",
         name="order_agent",
         # In a real application, an agent can have multiple tools; here we keep it simple
@@ -91,7 +91,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
     )
 
     # Return specialist: Handles return requests
-    return_agent = chat_client.create_agent(
+    return_agent = chat_client.as_agent(
         instructions="You manage product return requests.",
         name="return_agent",
         # In a real application, an agent can have multiple tools; here we keep it simple

python/samples/getting_started/workflows/agents/mixed_agents_and_executors.py

@@ -82,7 +82,7 @@ def create_coding_agent(client: AzureAIAgentClient) -> ChatAgent:
     Returns:
         A ChatAgent configured with coding instructions and tools
     """
-    return client.create_agent(
+    return client.as_agent(
         name="CodingAgent",
         instructions=("You are a helpful assistant that can write and execute Python code to solve problems."),
         tools=HostedCodeInterpreterTool(),

python/samples/getting_started/workflows/agents/sequential_workflow_as_agent.py

@@ -29,12 +29,12 @@ async def main() -> None:
     # 1) Create agents
     chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
-    writer = chat_client.create_agent(
+    writer = chat_client.as_agent(
         instructions=("You are a concise copywriter. Provide a single, punchy marketing sentence based on the prompt."),
         name="writer",
     )
 
-    reviewer = chat_client.create_agent(
+    reviewer = chat_client.as_agent(
         instructions=("You are a thoughtful reviewer. Give brief feedback on the previous assistant message."),
         name="reviewer",
     )

python/samples/getting_started/workflows/agents/workflow_as_agent_kwargs.py

@@ -79,7 +79,7 @@ async def main() -> None:
     chat_client = OpenAIChatClient()
 
     # Create agent with tools that use kwargs
-    agent = chat_client.create_agent(
+    agent = chat_client.as_agent(
         name="assistant",
         instructions=(
             "You are a helpful assistant. Use the available tools to help users. "

python/samples/getting_started/workflows/agents/workflow_as_agent_with_thread.py

@@ -40,7 +40,7 @@ async def main() -> None:
 
     # Define factory functions for workflow participants
     def create_assistant() -> ChatAgent:
-        return chat_client.create_agent(
+        return chat_client.as_agent(
             name="assistant",
             instructions=(
                 "You are a helpful assistant. Answer questions based on the conversation "
@@ -49,7 +49,7 @@ async def main() -> None:
         )
 
     def create_summarizer() -> ChatAgent:
-        return chat_client.create_agent(
+        return chat_client.as_agent(
             name="summarizer",
             instructions=(
                 "You are a summarizer. After the assistant responds, provide a brief "
@@ -124,7 +124,7 @@ async def demonstrate_thread_serialization() -> None:
     chat_client = OpenAIChatClient()
 
     def create_assistant() -> ChatAgent:
-        return chat_client.create_agent(
+        return chat_client.as_agent(
             name="memory_assistant",
             instructions="You are a helpful assistant with good memory. Remember details from our conversation.",
         )